Dataset Information

Risk adjustment models for interhospital comparison of CS rates using Robson's ten group classification system and other socio-demographic and clinical variables.

ABSTRACT:

Background

Caesarean section (CS) rate is a quality of health care indicator frequently used at national and international level. The aim of this study was to assess whether adjustment for Robson's Ten Group Classification System (TGCS), and clinical and socio-demographic variables of the mother and the fetus is necessary for inter-hospital comparisons of CS rates.

Methods

The study population includes 64,423 deliveries in Emilia-Romagna between January 1, 2003 and December 31, 2004, classified according to theTGCS. Poisson regression was used to estimate crude and adjusted hospital relative risks of CS compared to a reference category. Analyses were carried out in the overall population and separately according to the Robson groups (groups I, II, III, IV and V-X combined). Adjusted relative risks (RR) of CS were estimated using two risk-adjustment models; the first (M1) including the TGCS group as the only adjustment factor; the second (M2) including in addition demographic and clinical confounders identified using a stepwise selection procedure. Percentage variations between crude and adjusted RRs by hospital were calculated to evaluate the confounding effect of covariates.

Results

The percentage variations from crude to adjusted RR proved to be similar in M1 and M2 model. However, stratified analyses by Robson's classification groups showed that residual confounding for clinical and demographic variables was present in groups I (nulliparous, single, cephalic, ?37 weeks, spontaneous labour) and III (multiparous, excluding previous CS, single, cephalic, ?37 weeks, spontaneous labour) and IV (multiparous, excluding previous CS, single, cephalic, ?37 weeks, induced or CS before labour) and to a minor extent in groups II (nulliparous, single, cephalic, ?37 weeks, induced or CS before labour) and IV (multiparous, excluding previous CS, single, cephalic, ?37 weeks, induced or CS before labour).

Conclusions

The TGCS classification is useful for inter-hospital comparison of CS section rates, but residual confounding is present in the TGCS strata.

SUBMITTER: Colais P

PROVIDER: S-EPMC3570355 | biostudies-literature | 2012 Jun

REPOSITORIES: biostudies-literature

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Publications

Risk adjustment models for interhospital comparison of CS rates using Robson's ten group classification system and other socio-demographic and clinical variables.

Colais Paola P Fantini Maria P MP Fusco Danilo D Carretta Elisa E Stivanello Elisa E Lenzi Jacopo J Pieri Giulia G Perucci Carlo A CA

BMC pregnancy and childbirth 20120621

<h4>Background</h4>Caesarean section (CS) rate is a quality of health care indicator frequently used at national and international level. The aim of this study was to assess whether adjustment for Robson's Ten Group Classification System (TGCS), and clinical and socio-demographic variables of the mother and the fetus is necessary for inter-hospital comparisons of CS rates.<h4>Methods</h4>The study population includes 64,423 deliveries in Emilia-Romagna between January 1, 2003 and December 31, 20 ...[more]

PMID: 22720844

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Project description:BackgroundCaesarean delivery (CD) rates are commonly used as an indicator of quality in obstetric care and risk adjustment evaluation is recommended to assess inter-institutional variations. The aim of this study was to evaluate whether the Ten Group classification system (TGCS) can be used in case-mix adjustment.MethodsStandardized data on 15,255 deliveries from 11 different regional centers were prospectively collected. Crude Risk Ratios of CDs were calculated for each center. Two multiple logistic regression models were herein considered by using: Model 1- maternal (age, Body Mass Index), obstetric variables (gestational age, fetal presentation, single or multiple, previous scar, parity, neonatal birth weight) and presence of risk factors; Model 2- TGCS either with or without maternal characteristics and presence of risk factors. Receiver Operating Characteristic (ROC) curves of the multivariate logistic regression analyses were used to assess the diagnostic accuracy of each model. The null hypothesis that Areas under ROC Curve (AUC) were not different from each other was verified with a Chi Square test and post hoc pairwise comparisons by using a Bonferroni correction.ResultsCrude evaluation of CD rates showed all centers had significantly higher Risk Ratios than the referent. Both multiple logistic regression models reduced these variations. However the two methods ranked institutions differently: model 1 and model 2 (adjusted for TGCS) identified respectively nine and eight centers with significantly higher CD rates than the referent with slightly different AUCs (0.8758 and 0.8929 respectively). In the adjusted model for TGCS and maternal characteristics/presence of risk factors, three centers had CD rates similar to the referent with the best AUC (0.9024).ConclusionsThe TGCS might be considered as a reliable variable to adjust CD rates. The addition of maternal characteristics and risk factors to TGCS substantially increase the predictive discrimination of the risk adjusted model.

Dataset Information

Risk adjustment models for interhospital comparison of CS rates using Robson's ten group classification system and other socio-demographic and clinical variables.

Background

Methods

Results

Conclusions

Publications

Risk adjustment models for interhospital comparison of CS rates using Robson's ten group classification system and other socio-demographic and clinical variables.

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